Doctors are “Radically and Catastrophically” Wrong About Benefit of Tests

Doctors are “Radically and Catastrophically” Wrong About Benefit of Tests

Gross Over Estimate of Usefulness

Great article in Washington Post on October 5th by Daniel Morgan, an epidemiologist at University of Maryland School of Medicine how doctors are “radically and catastrophically wrong” about how useful a medical test will be and how “many thousands of patients are diagnosed with diseases they don’t have.”

How, for example, in one study gynecologists estimated that a woman whose mammogram was positive had a higher than 80 percent chance of having breast cancer. When the reality is, her chance is less than 10 percent.

Not Nearly the Risk of Cancer She Thinks

Nearly 90 percent of 177 patients reviewed “received at least one unnecessary test and that, overall, nearly one-third of all tests were superfluous.”

It’s not as if we’re not spending enough already on necessary tests.

“The companies that provide tests work hard to promote their products” notes Dr. Morgan. Patients should understand that even quite capable doctors “may not fully understand the statistical underpinning of the tests they use.”

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Great article in Washington Post on October 5th by Daniel Morgan, an epidemiologist at University of Maryland School of Medicine how doctors are “radically and catastrophically wrong” about how useful a medical test will be and how “many thousands of patients are diagnosed with diseases they don’t have.”
How, for example, in one study gynecologists estimated that a woman whose mammogram was positive had a higher than 80 percent chance of having breast cancer. When the reality is, her chance is less than 10 percent.
Nearly 90 percent of 177 patients reviewed “received at least one unnecessary test and that, overall, nearly one-third of all tests were superfluous.”
It’s not as if we’re not spending enough already on necessary tests.
“The companies that provide tests work hard to promote their products” notes Dr. Morgan. Patients should understand that even quite capable doctors “may not fully understand the statistical underpinning of the tests they use.”